Principles of Machine Learning by Sippo Rossi
Updated: Nov 3
Date: 4th and 11th of November 2022 in a hybrid format.
4th will be on campus (Tollbugata 17 1st Floor)
11th will be only online.
Time: 12:00 PM to 3:30PM
The Zoom link :
All materials that you will need during the course will be shared via this drive-folder where materials will be added soon: https://drive.google.com/drive/folders/1YCwkgwRECUVMX76IaM8wQL5jEhP_rBjP?usp=share_link
Duration: 8 hours
Learn the basics of unsupervised and supervised machine learning methods and practice using them in Python with scikit-learn. Recommended for everyone.
Sign Up: https://forms.gle/4E4y56KLqpCsAm5NA
What you will learn
The skills listed below are taught in the two days of the course and students are also granted access to additional self-paced eLearning materials where they can practice and learn more.
· What is unsupervised and supervised machine learning
· How to pre-process your data for machine learning
· How to use Python and scikit-learn to create machine learning models
· How to use various clustering algorithms to group data
· How to use different supervised machine learning algorithms to solve classification and regression tasks
What is offered
In addition to the 8 hour training, we offer the following:
· Some fun working with data
· A community of students and staff interested in data analytics
· Free 6-month licenses to Datacamp (https://www.datacamp.com) which will allow independently learn more before and after the workshop
· The course requires no previous experience in machine learning
· Participants should be comfortable with using Python (having completed 1 university level course is sufficient)
· Participants should be able to manipulate data using Python libraries such as NumPy and Pandas
· Participants need to have their own laptop. It is recommended that you bring a power cord for your own device.
· Participants should have Anaconda (Individual Edition) installed on their laptop (https://www.anaconda.com/products/individual) before the start of the first session.
About the trainer
Sippo is a PhD Fellow at Copenhagen Business School, who uses machine learning to detect and study bots on social networking sites such as Twitter. He also teaches in master’s level courses related to data mining and machine learning at CBS.
Note! Students who sign up will be given Datacamp licenses in advance and recommended courses to complete there that will give sufficient knowledge to complete the course if the above requirements are not met already.
In case of questions please contact us at LesterAllan.Lasrado@kristiania.no